Generally, SIMD is a technique employed to achieve data level parallelism. In particular, multiple data may be processed in multiple corresponding lanes of an SIMD engine in accordance with a single instruction.
SIMD can be used to speed up processing of graphics data, including the K-Nearest-Neighbors (KNN) algorithm. The KNN algorithm is generally used for classification or regression analysis in pattern recognition.